Magnetic resonance imaging (MRI) may be used in conjunction with ultrasound focusing, or other non-invasive treatment modalities, in a variety of medical applications. Ultrasound penetrates well through soft tissues and, due to its short wavelengths, can be focused to spots with dimensions of a few millimeters. As a consequence of these properties, ultrasound can be used for non-invasive, highly localized surgery—for example, to ablate or coagulate cancerous tissue without causing significant damage to surrounding healthy tissue. An ultrasound focusing system generally utilizes an acoustic transducer surface, or an array of transducer surfaces, to generate an ultrasound beam. The transducer may be geometrically shaped and positioned such that the ultrasonic energy is focused at a “focal zone” corresponding to the target tissue mass within the patient. During wave propagation through the tissue, a portion of the ultrasound energy is absorbed, leading to increased temperature and, eventually, to cellular necrosis—preferably at the target tissue mass in the focal zone. The individual surfaces, or “elements,” of the transducer array are typically individually controllable, i.e., their phases and/or amplitudes can be set independently of one another (e.g., using a “beamformer” with suitable delay and amplifier circuitry for the elements), allowing the beam to be steered in a desired direction and focused at a desired distance and the focal zone properties to be shaped as needed. Thus, the focal zone can be rapidly displaced and/or reshaped by independently adjusting the amplitudes and phases of the electrical signal input into the transducer elements.
In MRI-guided focused-ultrasound (MRgFUS) methods, MRI serves to visualize both the target tissue and the ultrasound focus. Generally, an MRI system 100, as depicted in FIG. 1, includes a static-field magnet 102, one or more gradient-field coils 104, a radio-frequency (RF) transmitter 106, and an RF receiver (not shown). (In some embodiments, the same device is used alternately as RF transmitter or receiver.) The magnet includes a region 108 for receiving a patient 110 therein, and provides a static, relatively homogeneous magnetic field over the patient. Time-variable magnetic field gradients generated by the gradient-field coils 104 are superposed with the static magnetic field. The RF transmitter 106 transmits RF pulse sequences over the patient 110 to cause the patient's tissues to emit a (time-varying) RF response signal, which is integrated over the entire (two- or three-dimensional) imaging region and sampled by the RF receiver to produce a time series of response signals that constitute the raw image data. This raw data is passed on to a computation unit 112. Each data point in the time series can be interpreted as the value of the Fourier transform of the position-dependent local magnetization at a particular point in k-space (i.e., wavevector space), where the wavevector k is a function of the time development of the gradient fields. Thus, by Fourier-transforming the time series of the response signal, the computation unit 112 can reconstruct a real-space image of the tissue (i.e., an image showing the measured magnetization-affecting tissue properties as a function of spatial coordinates) from the raw data. The real-space magnetic-resonance (MR) image may then be displayed to the user. The MRI system 100 may be used to plan a medical procedure, as well as to monitor treatment progress during the procedure. For example, MRI may be used to image an anatomical region, locate the target tissue (e.g., a tumor) within the region, guide the beam generated by the ultrasound transducer 114 to the target tissue, and/or monitor the temperature in and surrounding the target tissue.
Patient motion during treatment, such as periodic motion due to respiration or random movements, can pose a considerable challenge to therapeutic efficacy and safety. Compensation for motion is necessary to ensure that the ultrasound beam remains focused on the target and does not damage the surrounding healthy tissues. In image-guided systems (such as MRgFUS systems), motion compensation is generally accomplished by tracking the target (directly or indirectly) in the images and steering the ultrasound beam based on the tracked position. One approach to target tracking involves determining the coordinates of a set of one or more identifiable features, or “anatomical landmarks,” that can be located in each image; and computing the motion of the target, which is presumed to be at a fixed location relative to the landmarks, based on these coordinates. In an alternative approach, the relative shifts between successive images are determined by correlating one image with a large number of computationally shifted copies of the other image, and selecting the shifted image that provides the best match. In either case, significant image-processing time is expended to determine the target location, reducing the effective imaging rate and often impeding real-time motion compensation. In some cases, delays in recognizing and quantifying target motion cause beam-targeting inaccuracies within a tolerable range. Often, however, it becomes necessary to stop the treatment process and correct for any misalignment due to displacement of the target tissue or organ before treatment can be resumed. This results in significant inefficiencies in the treatment process, and may generate significant delays.
Accordingly, there is a need for improved motion-tracking approaches that facilitate tracking the target, and compensating for its motion, in real time during treatment.